This paper presents an original approach based on a recent metric called feature maximization for developing accurate diachronic analysis tools. In such process, querying of bibliographic databases is firstly exploited to provide a thematic corpus of scientific publications covering a large time period. In a second step, two strategies based on contrast graphs generated by the use of feature maximization metric are proposed. The first one is based on the direct use contrast graphs who relates time periods and publication contents. The second strategy combines a preliminary step of clustering with the use of contrast graph generated by feature maximization applied on cluster contents to highlight the relation between topics represented in clusters as well as to embed them in a temporal path. Both techniques are parameter-free and knowledge agnostic. We illustrate the efficiency and the complementarity of the proposed technique by experimenting then on a dataset related to gerontology research extracted from the data collected by the ISTEX project, a project whose aims is to construct a general purpose and open access database of scientific documents.